Birding, that is the recreational activity of observing birds, is an increasingly popular pastime around the world. An important component of birding is the identification of the species of an observed bird. At least as important to the birder is the identification of the genus or family, of an observed bird, especially if the species is unknown. Of special importance to serious birders is aiding their accomplishment of learning to identify observed birds in the field.
To date, birders have had only field guides and recordings as personal aids for identifying and learning to identify birds. However, in no case do these aids actually determine an identification, they only provide comparative references and the judgment of whether a match is made or not is left entirely to the birder. Further, in no case is any feedback given on the quality or reliability of the match they have just made, Additionally, in the case of learning bird songs and calls, there is currently no practical way to precisely indicate to the learner which aspects of a particular bird's song are most relevant to the identification. In consequence, making progress in learning identification is slow at best.
More recently, there have been electronic versions of field guides created (sometimes including audio recordings) that speed the process of searching for a particular comparative reference. However, even with these more sophisticated approaches, the ultimate judgment about a match is left entirely to the birder and no feedback on the quality of their match is provided, or even possible.
For other birders, such as people who set out bird feeders in their backyard, the joy of knowing what birds have visited their yard is foremost and learning the skill of identifying the birds is not as important. For these birders, field guides and recordings, electronic or not, have another significant liability. This liability is that the birder must be actively engaged in birding at the time a bird shows up in their yard in order to make the identification. Every backyard birder will surely identify with the experience of noticing an interesting bird, perhaps by hearing its unusual song, and running to get a field guide only to discover that the bird has left by the time they get back to make the identification.
The current invention teaches how to overcome all the deficiencies noted above with an apparatus that automatically identifies birds by way of their vocalizations (calls and songs) and employs a novel method for doing so. Previous methods for attempting to identify birds by their vocalizations such as neural network, hidden Markov model, dynamic time warping, and other techniques, attempt to match an incoming bird vocalization against a library of exemplars using an overall similarity standard to determine a match. These techniques have not achieved notable success in resolving any of the deficiencies noted above.
The current invention takes a different approach. Instead of an overall similarity standard, the current invention, as described in detail below, employs a hierarchical method that largely parallels the neuro-physiological hierarchy of bird vocalizations. When this method is embodied in a very portable computing device, such as a personal digital assistant augmented with appropriate software and audio capture capability, this method allows the device to determine that a bird is singing, even if nothing else about the bird can be determined. Further, it allows the family of a bird to be determined, even if the species cannot be determined. Finally, it allows the species to be determined. Additionally, it provides for the time-based annotation of the bird song so that that the relative importance of each part of the song for the purpose of identification can be relayed to the birder to aid in their learning.
The current invention teaches how to embody such functionality in a hand-held computational device together with a microphone, an audio capture card or other means, a user application that runs on the device, and a library of vocalization characteristics that, because it resides on the audio capture card, is accessible to the application but generally inaccessible to the user. This last characteristic allows for new libraries of characteristics to be sold as hardware additions, lessening the problem of unauthorized distribution.
The intended use of this invention is two-fold. When a birder carrying the device hears a bird of interest while observing birds in the field, they point the microphone of the device toward the calling bird and activate the identification function of the device. The device processes the sound and presents the results of the analysis to the birder. The possible results include that no bird was detected; that a bird was detected but the family could not be determined; that a bird was detected and the family was identified (and was so and so), but the species could not be determined; that a bird was detected, the family was determined (and was so and so) and the species was determined to be so and so.
Alternatively, the device can be used in backyard mode in which all incoming sounds are analyzed and when a bird is detected the device automatically proceeds with the identification process and records the results for the birder to review immediately or at a later time.